摘要
针对房价增长过快的问题,该文以赣州市2017年的房产交易数据为研究对象,通过计算Moran’s I指数和Getis-Ord G指数分析了房价的空间相关性和空间异质性,并筛选出地块属性、商服繁华因素、交通因素、公共设施因素以及环境因素,结合灰色关联模型对中小城市房价的影响因素进行了分析。结果表明:赣州市房价在总体上呈现显著的空间相关性,且大部分住宅在空间上表现出集聚特征,小部分住宅由于在空间上存在异质性,表现出离散特征;房价自相关的阈值范围为5.2 km;房价的热点区主要分布在万象城,城市中央公园附近,冷点区主要分布在沙河镇区域;灰色关联模型分析表明,小区绿化率,市中心对房价的影响最大,容积率、交通枢纽、医院对房价的影响次之;学校、商场、公园、建筑面积以及河流对房价的影响较弱。
In response to the problem that house prices are growing too fast.this paper took the real estate transaction data of Ganzhou city in 2017 as the research object,analyzed the spatial correlation and spatial heterogeneity of house prices by calculating Moran's 1 index and Getis Ord G index,and screened out the property-of the plot to discuss the prosperous factors,traffic factors,public facilities factors and environmental factors,combined with the gray correlation model,analyzed the factors affecting the housing prices of small and medium-sized cities.The results showed that the housing prices in Ganzhou city showed a significant spatial correlation,and most of the houses showed agglomeration characteristics in space.Due to the heterogeneity in space,a small number of houses exhibit discrete characteristics,and the threshold range of house price autocorrelation was 5.2 km;the Hot spots were mainly distributed in Vientiane city,near the city's Central Park,and the Cold spots were mainly distributed in the Shahe Town area;the grey relational model analysis showed that the greening rate of residential area and the location of urban center had the greatest impact on housing prices,and the volume rate,transportation hub and hospital had the second impact on housing prices,while the impact of schools,shopping malls,parks,building areas and rivers on housing prices was weak.
作者
张哲源
王秀丽
李恒凯
ZHANG Zheyuan;WANG Xiuli;LI Hengkai(College of Economic Management,Jiangxi University of Science and Technology,Ganzhou,Jiangxi 341000,China;School of Architectural and Surveying&.Mapping Engineering,Jiangxi University of Science and Technology,Ganzhou,Jiangxi 341000,China)
出处
《测绘科学》
CSCD
北大核心
2020年第6期172-179,共8页
Science of Surveying and Mapping
基金
江西省社会科学规划课题项目(17YJ20)。
关键词
房价
空间分布
灰色关联度
影响因素
house price
spatial distribution
grey correlation
influencing factor
